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Jadick G, Abadi E, Harrawood B, Sharma S, Segars WP, Samei E. A scanner-specific framework for simulating CT images with tube current modulation. Phys Med Biol 2021; 66. [PMID: 34464942 DOI: 10.1088/1361-6560/ac2269] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 08/31/2021] [Indexed: 11/12/2022]
Abstract
Although tube current modulation (TCM) is routinely implemented in modern computed tomography (CT) scans, no existing CT simulator is capable of generating realistic images with TCM. The goal of this study was to develop such a framework to (1) facilitate patient-specific optimization of TCM parameters and (2) enable future virtual imaging trials (VITs) with more clinically realistic image quality and x-ray flux distributions. The framework was created by developing a TCM module and integrating it with an existing CT simulator (DukeSim). The developed module utilizes scanner-calibrated TCM parameters and two localizer radiographs to compute the mAs for each simulated CT projection. This simulation pipeline was validated in two parts. First, DukeSim was validated in the context of a commercial scanner with TCM (SOMATOM Force, Siemens Healthineers) by imaging a physical CT phantom (Mercury, Sun Nuclear) and its computational analogue. Second, the TCM module was validated by imaging a computational anthropomorphic phantom (ATOM, CIRS) using DukeSim with real and module-generated TCM profiles. The validation demonstrated DukeSim's realism in terms of noise magnitude, noise texture, spatial resolution, and image contrast (with average differences of 0.38%, 6.31%, 0.43%, and -9 HU, respectively). It also demonstrated the TCM module's realism in terms of projection-level mAs and resulting noise magnitude (2.86% and -2.60%, respectively). Finally, the framework was applied to a pilot VIT simulating images of three computational anthropomorphic phantoms (XCAT, with body mass indices (BMIs) of 24.3, 28.2, and 33.0) under five different TCM settings. The optimal TCM for each phantom was characterized based on various criteria, such as minimizing mAs or maximizing image quality. 'Very Weak' TCM minimized noise for the 24.3 BMI phantom, while 'Very Strong' TCM minimized noise for the 33.0 BMI phantom. This illustrates the utility of the developed framework for future optimization studies of TCM parameters and, more broadly, large-scale VITs with scanner-specific TCM.
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Affiliation(s)
- Giavanna Jadick
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
| | - Ehsan Abadi
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America.,Medical Physics Graduate Program, Duke University School of Medicine, NC, United States of America.,Department of Electrical and Computer Engineering, Duke University, NC, United States of America
| | - Brian Harrawood
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America
| | - Shobhit Sharma
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America.,Department of Physics, Duke University, NC, United States of America
| | - W Paul Segars
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America.,Medical Physics Graduate Program, Duke University School of Medicine, NC, United States of America.,Department of Biomedical Engineering, Duke University, NC, United States of America
| | - Ehsan Samei
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, NC, United States of America.,Medical Physics Graduate Program, Duke University School of Medicine, NC, United States of America.,Department of Electrical and Computer Engineering, Duke University, NC, United States of America.,Department of Physics, Duke University, NC, United States of America.,Department of Biomedical Engineering, Duke University, NC, United States of America
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Gould SM, Mackewn J, Chicklore S, Cook GJR, Mallia A, Pike L. Optimisation of CT protocols in PET-CT across different scanner models using different automatic exposure control methods and iterative reconstruction algorithms. EJNMMI Phys 2021; 8:58. [PMID: 34331602 PMCID: PMC8325723 DOI: 10.1186/s40658-021-00404-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 07/13/2021] [Indexed: 11/20/2022] Open
Abstract
Background A significant proportion of the radiation dose from a PET-CT examination is dependent on the CT protocol, which should be optimised for clinical purposes. Matching protocols on different scanners within an imaging centre is important for the consistency of image quality and dose. This paper describes our experience translating low-dose CT protocols between scanner models utilising different automatic exposure control (AEC) methods and reconstruction algorithms. Methods The scanners investigated were a newly installed Siemens Biograph mCT PET with 64-slice SOMATOM Definition AS CT using sinogram affirmed iterative reconstruction (SAFIRE) and two GE Discovery 710 PET scanners with 128-slice Optima 660 CT using adaptive statistical reconstruction (ASiR). Following exploratory phantom work, 33 adult patients of various sizes were scanned using the Siemens scanner and matched to patients scanned using our established GE protocol to give 33 patient pairs. A comparison of volumetric CT dose index (CTDIvol) and image noise within these patient pairs informed optimisation, specifically for obese patients. Another matched patient study containing 27 patient pairs was used to confirm protocol matching. Size-specific dose estimates (SSDEs) were calculated for patients in the second cohort. With the acquisition protocol for the Siemens scanner determined, clinicians visually graded the images to identify optimal reconstruction parameters. Results In the first matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 10.7% (range − 41.7 to 50.1%), and the mean percentage difference in noise measured in the patients’ liver was 7.6% (range − 31.0 to 76.8%). In the second matched patient study, the mean percentage difference in CTDIvol for Siemens compared to GE was − 20.5% (range − 43.1 to 1.9%), and the mean percentage difference in noise was 19.8% (range − 27.0 to 146.8%). For these patients, the mean SSDEs for patients scanned on the Siemens and GE scanners were 3.27 (range 2.83 to 4.22) mGy and 4.09 (range 2.81 to 4.82) mGy, respectively. The analysis of the visual grading study indicated no preference for any of the SAFIRE strengths. Conclusions Given the different implementations of acquisition parameters and reconstruction algorithms between vendors, careful consideration is required to ensure optimisation and standardisation of protocols.
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Affiliation(s)
- Sarah-May Gould
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK.
| | - Jane Mackewn
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Sugama Chicklore
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Gary J R Cook
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Andrew Mallia
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Lucy Pike
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
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Anam C, Budi WS, Adi K, Sutanto H, Haryanto F, Ali MH, Fujibuchi T, Dougherty G. Assessment of patient dose and noise level of clinical CT images: automated measurements. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2019; 39:783-793. [PMID: 31117064 DOI: 10.1088/1361-6498/ab23cc] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
We investigated comparisons between patient dose and noise in pelvic, abdominal, thoracic and head CT images using an automatic method. 113 patient images (37 pelvis, 34 abdominal, 25 thoracic, and 17 head examinations) were retrospectively and automatically examined in this study. Water-equivalent diameter (Dw), size-specific dose estimates (SSDE) and noise were automatically calculated from the center slice for every patient image. The Dw was calculated based on auto-contouring of the patients' edges, and the SSDE was calculated as the product of the volume CT dose index (CTDIvol) extracted from the Digital Imaging and Communications in Medicine (DICOM) header and the size conversion factor based on the Dw obtained from AAPM 204. The noise was automatically measured as a minimum standard deviation in the map of standard deviations. A square region of interest of about 1 cm2 was used in the automated noise measurement. The SSDE values for the pelvis, abdomen, thorax, and head were 21.8 ± 7.3 mGy, 22.0 ± 4.5 mGy, 21.5 ± 4.7 mGy, and 65.1 ± 1.7 mGy, respectively. The SSDEs for the pelvis, abdomen, and thorax increased linearly with increasing Dw, and for the head with constant tube current, the SSDE decreased with increasing Dw. The noise in the pelvis, abdomen, thorax, and head were 5.9 ± 1.5 HU, 5.2 ± 1.4 HU, 4.9 ± 0.8 HU and 3.9 ± 0.2 HU, respectively. The noise levels for the pelvis, abdomen, and thorax of the patients were relatively constant with Dw because of tube current modulation. The noise in the head image was also relatively constant because Dw variations in the head are very small. The automated approach provides a convenient and objective tool for dose optimizations.
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Affiliation(s)
- Choirul Anam
- Department of Physics, Faculty of Mathematics and Natural Sciences, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
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Hardy AJ, Angel E, Bostani M, Cagnon C, McNitt-Gray M. Estimating fetal dose from tube current-modulated (TCM) and fixed tube current (FTC) abdominal/pelvis CT examinations. Med Phys 2019; 46:2729-2743. [PMID: 30893477 DOI: 10.1002/mp.13499] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Revised: 03/12/2019] [Accepted: 03/13/2019] [Indexed: 11/05/2022] Open
Abstract
PURPOSE The purpose of this work was to estimate scanner-independent CTDIvol -to-fetal-dose coefficients for tube current-modulated (TCM) and fixed tube current (FTC) computed tomography (CT) examinations of pregnant patients of various gestational ages undergoing abdominal/pelvic CT examinations. METHODS For 24 pregnant patients of gestational age from <5 to 36 weeks who underwent clinically indicated CT examinations, voxelized models of maternal and fetal (or embryo) anatomy were created from abdominal/pelvic image data. Absolute fetal dose (Dfetus ) was estimated using Monte Carlo (MC) simulations of helical scans covering the abdomen and pelvis for TCM and FTC scans. Estimated TCM schemes were generated for each patient model using a validated method that accounts for patient attenuation and scanner output limits for one scanner model and were incorporated into MC simulations. FTC scans were also simulated for each patient model with multidetector row CT scanners from four manufacturers. Normalized fetal dose estimates, nDfetus , was obtained by dividing Dfetus from the MC simulations by CTDIvol . Patient size was described using water equivalent diameter (Dw ) measured at the three-dimensional geometric centroid of the fetus. Fetal depth (DEf ) was measured from the anterior skin surface to the anterior part of the fetus. nDfetus and Dw were correlated using an exponential model to develop equations for fetal dose conversion coefficients for TCM and FTC abdominal/pelvic CT examinations. Additionally, bivariate linear regression was performed to analyze the correlation of nDfetus with Dw and fetal depth (DEf ). For one scanner model, nDfetus from TCM was compared to FTC and the size-specific dose estimate (SSDE) conversion coefficients (f-factors) from American Association of Physicists in Medicine (AAPM) Report 204. nDfetus from FTC simulations was averaged across all scanners for each patient ( n D fetus ¯ ) . n D fetus ¯ was then compared with SSDE f-factors and correlated with Dw using an exponential model and with Dw and DEf using a bivariate linear model. RESULTS For TCM, the coefficient of determination (R2 ) of nDfetus and Dw was observed to be 0.73 using an exponential model. Using the bivariate linear model with Dw and DEf , an R2 of 0.78 was observed. For the TCM technology modeled, TCM yielded nDfetus values that were on average 6% and 17% higher relative to FTC and SSDE f-factors, respectively. For FTC, the R2 of n D fetus ¯ with respect to Dw was observed to be 0.64 using an exponential model. Using the bivariate linear model, an R2 of 0.75 was observed for n D fetus ¯ with respect to Dw and DEf . A mean difference of 0.4% was observed between n D fetus ¯ and SSDE f-factors. CONCLUSION Good correlations were observed for nDfetus from TCM and FTC scans using either an exponential model with Dw or a bivariate linear model with both Dw and DEf . These results indicate that fetal dose from abdomen/pelvis CT examinations of pregnant patients of various gestational ages may be reasonably estimated with models that include (a) scanner-reported CTDIvol and (b) Dw as a patient size metric, in addition to (c) DEf if available. These results also suggest that SSDE f-factors may provide a reasonable (within ±25%) estimate of nDfetus for TCM and FTC abdomen/pelvis CT exams.
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Affiliation(s)
- Anthony J Hardy
- Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Erin Angel
- Canon Medical Systems USA, Inc., Tustin, CA, 92780, USA
| | - Maryam Bostani
- Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Chris Cagnon
- Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Michael McNitt-Gray
- Department of Radiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Physics and Biology in Medicine Graduate Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
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Khobragade P, Rupcich F, Fan J, Crotty DJ, Kulkarni NM, O'Connor SD, Foley WD, Schmidt TG. CT automated exposure control using a generalized detectability index. Med Phys 2018; 46:140-151. [PMID: 30417403 DOI: 10.1002/mp.13286] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 10/07/2018] [Accepted: 10/26/2018] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Identifying an appropriate tube current setting can be challenging when using iterative reconstruction due to the varying relationship between spatial resolution, contrast, noise, and dose across different algorithms. This study developed and investigated the application of a generalized detectability index ( d gen ' ) to determine the noise parameter to input to existing automated exposure control (AEC) systems to provide consistent image quality (IQ) across different reconstruction approaches. METHODS This study proposes a task-based automated exposure control (AEC) method using a generalized detectability index ( d gen ' ). The proposed method leverages existing AEC methods that are based on a prescribed noise level. The generalized d gen ' metric is calculated using lookup tables of task-based modulation transfer function (MTF) and noise power spectrum (NPS). To generate the lookup tables, the American College of Radiology CT accreditation phantom was scanned on a multidetector CT scanner (Revolution CT, GE Healthcare) at 120 kV and tube current varied manually from 20 to 240 mAs. Images were reconstructed using a reference reconstruction algorithm and four levels of an in-house iterative reconstruction algorithm with different regularization strengths (IR1-IR4). The task-based MTF and NPS were estimated from the measured images to create lookup tables of scaling factors that convert between d gen ' and noise standard deviation. The performance of the proposed d gen ' -AEC method in providing a desired IQ level over a range of iterative reconstruction algorithms was evaluated using the American College of Radiology (ACR) phantom with elliptical shell and using a human reader evaluation on anthropomorphic phantom images. RESULTS The study of the ACR phantom with elliptical shell demonstrated reasonable agreement between the d gen ' predicted by the lookup table and d ' measured in the images, with a mean absolute error of 15% across all dose levels and maximum error of 45% at the lowest dose level with the elliptical shell. For the anthropomorphic phantom study, the mean reader scores for images resulting from the d gen ' -AEC method were 3.3 (reference image), 3.5 (IR1), 3.6 (IR2), 3.5 (IR3), and 2.2 (IR4). When using the d gen ' -AEC method, the observers' IQ scores for the reference reconstruction were statistical equivalent to the scores for IR1, IR2, and IR3 iterative reconstructions (P > 0.35). The d gen ' -AEC method achieved this equivalent IQ at lower dose for the IR scans compared to the reference scans. CONCLUSIONS A novel AEC method, based on a generalized detectability index, was investigated. The proposed method can be used with some existing AEC systems to derive the tube current profile for iterative reconstruction algorithms. The results provide preliminary evidence that the proposed d gen ' -AEC can produce similar IQ across different iterative reconstruction approaches at different dose levels.
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Affiliation(s)
- P Khobragade
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, 53233, USA
| | | | | | | | | | | | | | - Taly Gilat Schmidt
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, 53233, USA
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McMillan K, Bostani M, Cagnon CH, Yu L, Leng S, McCollough CH, McNitt-Gray MF. Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values. Med Phys 2017; 44:4262-4275. [PMID: 28477342 DOI: 10.1002/mp.12314] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 04/04/2017] [Accepted: 04/09/2017] [Indexed: 02/05/2023] Open
Abstract
PURPOSE The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose. METHODS Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual-topo and sim-topo). RESULTS When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual-topo) and simulated topogram (sim-topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual-topo and sim-topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%. CONCLUSIONS Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data.
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Affiliation(s)
- Kyle McMillan
- Biomedical Physics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Maryam Bostani
- Biomedical Physics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Christopher H Cagnon
- Biomedical Physics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Lifeng Yu
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Shuai Leng
- Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - Michael F McNitt-Gray
- Biomedical Physics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90024, USA
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Punnoose J, Xu J, Sisniega A, Zbijewski W, Siewerdsen JH. Technical Note: spektr 3.0-A computational tool for x-ray spectrum modeling and analysis. Med Phys 2016; 43:4711. [PMID: 27487888 PMCID: PMC4958109 DOI: 10.1118/1.4955438] [Citation(s) in RCA: 109] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2016] [Revised: 06/13/2016] [Accepted: 06/24/2016] [Indexed: 12/24/2022] Open
Abstract
PURPOSE A computational toolkit (spektr 3.0) has been developed to calculate x-ray spectra based on the tungsten anode spectral model using interpolating cubic splines (TASMICS) algorithm, updating previous work based on the tungsten anode spectral model using interpolating polynomials (TASMIP) spectral model. The toolkit includes a matlab (The Mathworks, Natick, MA) function library and improved user interface (UI) along with an optimization algorithm to match calculated beam quality with measurements. METHODS The spektr code generates x-ray spectra (photons/mm(2)/mAs at 100 cm from the source) using TASMICS as default (with TASMIP as an option) in 1 keV energy bins over beam energies 20-150 kV, extensible to 640 kV using the TASMICS spectra. An optimization tool was implemented to compute the added filtration (Al and W) that provides a best match between calculated and measured x-ray tube output (mGy/mAs or mR/mAs) for individual x-ray tubes that may differ from that assumed in TASMICS or TASMIP and to account for factors such as anode angle. RESULTS The median percent difference in photon counts for a TASMICS and TASMIP spectrum was 4.15% for tube potentials in the range 30-140 kV with the largest percentage difference arising in the low and high energy bins due to measurement errors in the empirically based TASMIP model and inaccurate polynomial fitting. The optimization tool reported a close agreement between measured and calculated spectra with a Pearson coefficient of 0.98. CONCLUSIONS The computational toolkit, spektr, has been updated to version 3.0, validated against measurements and existing models, and made available as open source code. Video tutorials for the spektr function library, UI, and optimization tool are available.
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Affiliation(s)
- J Punnoose
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205
| | - J Xu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205
| | - A Sisniega
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205
| | - W Zbijewski
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205
| | - J H Siewerdsen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205
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Favazza CP, Duan X, Zhang Y, Yu L, Leng S, Kofler JM, Bruesewitz MR, McCollough CH. A cross-platform survey of CT image quality and dose from routine abdomen protocols and a method to systematically standardize image quality. Phys Med Biol 2015; 60:8381-97. [PMID: 26459751 DOI: 10.1088/0031-9155/60/21/8381] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Through this investigation we developed a methodology to evaluate and standardize CT image quality from routine abdomen protocols across different manufacturers and models. The influence of manufacturer-specific automated exposure control systems on image quality was directly assessed to standardize performance across a range of patient sizes. We evaluated 16 CT scanners across our health system, including Siemens, GE, and Toshiba models. Using each practice's routine abdomen protocol, we measured spatial resolution, image noise, and scanner radiation output (CTDIvol). Axial and in-plane spatial resolutions were assessed through slice sensitivity profile (SSP) and modulation transfer function (MTF) measurements, respectively. Image noise and CTDIvol values were obtained for three different phantom sizes. SSP measurements demonstrated a bimodal distribution in slice widths: an average of 6.2 ± 0.2 mm using GE's 'Plus' mode reconstruction setting and 5.0 ± 0.1 mm for all other scanners. MTF curves were similar for all scanners. Average spatial frequencies at 50%, 10%, and 2% MTF values were 3.24 ± 0.37, 6.20 ± 0.34, and 7.84 ± 0.70 lp cm(-1), respectively. For all phantom sizes, image noise and CTDIvol varied considerably: 6.5-13.3 HU (noise) and 4.8-13.3 mGy (CTDIvol) for the smallest phantom; 9.1-18.4 HU and 9.3-28.8 mGy for the medium phantom; and 7.8-23.4 HU and 16.0-48.1 mGy for the largest phantom. Using these measurements and benchmark SSP, MTF, and image noise targets, CT image quality can be standardized across a range of patient sizes.
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